Computer Vision Engineer

About Fogsphere

Fogsphere is a London‑based innovator focused on transforming workplace and urban safety through advanced AI, Computer Vision, and Industrial IoT. Built on a principled "Edge‑to‑Fog‑to‑Cloud" architecture, our platform turns passive CCTV cameras and sensors into proactive hazard detectors, capable of identifying threats like missing PPE, fire, smoke, restricted access violations, and more-in real time and at scale. This helps organizations across industries-from manufacturing, construction, oil & gas, and healthcare to smart cities-reduce workplace accidents by up to 90%, ensure regulatory compliance (EHS), and gain powerful operational insights. Fogsphere's intuitive no‑code visual workflows, hyper‑scalable Kubernetes‑based infrastructure, and commitment to ethical AI and privacy (GDPR compliance) make it a user‑friendly yet enterprise‑grade solution.

About the Role

We are seeking a highly motivated Computer Vision Engineer with a strong background in Deep Learning to join our AI/ML team. You will focus on developing, training, and optimizing models for computer vision applications, working with large-scale image/video datasets, and deploying cutting-edge deep learning solutions into production environments.

Key Responsibilities

Design, train, and evaluate deep learning models for computer vision tasks (e.g., classification, detection, segmentation, tracking, retrieval...).

VLM fine-tuning.

Build and maintain scalable data pipelines for training and evaluation.

Optimize model architectures for performance, accuracy, and efficiency (e.g., pruning, quantization, distributed training).

Contribute to research and prototyping of novel computer vision algorithms.

Deploy trained models into production environments in collaboration with software engineering teams.

Document workflows and contribute to team knowledge-sharing.

Qualifications

MSc in Computer Vision, Machine Learning, Artificial Intelligence, or related field.

2+ years of hands-on experience in deep learning model development and training.

Strong proficiency with Python and ML frameworks (PyTorch, TensorFlow, or Keras).

Solid understanding of CNNs, and ViTs

Experience with dataset preparation, augmentation, and preprocessing for computer vision.

Strong knowledge of optimization techniques, hyperparameter tuning, and evaluation metrics.

Good software engineering practices: version control (Git), code testing, reproducibility.

Experience working with MLOps frameworks (e.g., MLflow, Weights & Biases, Kubeflow).

Preferred Skills (nice-to-have)

Experience on VLM fine-tuning.

Knowledge of cloud platforms (AWS, GCP, Azure) for model training and deployment.

Background in multimodal AI (vision + language).

Contributions to open-source CV/ML projects or publications in top conferences (CVPR, ICCV, NeurIPS, ECCV, TPAMI...).

Knowledge on TRT.

Experience on edge computing applications.

Experience on ANPR and/or Face Recognition, and/or Image Retrieval in general.

What We Offer

ZERO micromanagement. At Fogsphere, researchers work independently under the Head of Research, with a focus on open discussion and professional development, where the best ideas are the ones applied.

Opportunity to work on cutting-edge computer vision challenges in some of the largest deployments in the field.

Possibility to publish papers and collaborate with academia on this task.

Collaborative environment with a team of AI researchers and engineers based on multiple countries.

Working with academics in the field to help building cutting-edge methods.

Competitive salary and benefits package.

Career growth and continuous learning opportunities.